Adhesion of corneal epithelial cells to cell adhesion peptide modified pHEMA surfaces
Bibliographic record
Abstract
Epithelialization of a corneal implant is a desirable property. In this study we compared surface modification of poly (2-hydroxyethyl methacrylate) (pHEMA) with the cell adhesion peptides RGDS and YIGSR. Various parameters in the tresyl chloride activation and modification reactions were considered in order to maximize surface coverage with the peptide including tresyl chloride reaction solvent. tresyl chloride reaction time, tresyl chloride concentration, peptide concentration, and peptide reaction pH. Surface chemistry and corneal epithelial cell adhesion to the modified surfaces were examined. X-ray photoelectron spectroscopy data suggested that while peptide modification had occurred, surface coverage with the peptide was incomplete. Acetone was found to result in a higher fraction of nitrogen and surface bound carboxyl groups compared to dioxane and ether. Furthermore, corneal epithelial cell adhesion to the surfaces for which acetone was used for the activation reaction was significantly greater. Statistical analysis of the various samples suggests that lower peptide concentrations and higher tresyl chloride reaction times result in better cell adhesion. Furthermore, modification with YIGSR resulted in higher surface concentrations and better cell adhesion than modification with RGDS. Little or no cell adhesion was noted on the unmodified pHEMA controls. Protein adsorption results suggest that the differences in cell adhesion cannot be attributed to differences in serum protein adsorption from the culture medium. We conclude that YIGSR modified surfaces have significant potential for further development in corneal applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".